Spatial dependency and correlation of properties of soil cultivated with oil palm, Elaeis guineensis, in agroforestry systems in the eastern Brazilian Amazon

Silva, Camila Santos da; Mendonça, Bruno Araújo Furtado de; Pereira, Marcos Gervásio; Araújo, Emanuel José Gomes de; Castellani, Debora

doi:10.1590/1809-4392201704423

Cited by 8 publications

(5 citation statements)

References 17 publications

(17 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a result, both topsoil SOM and TN increase seasonally (Figure 2). Soil properties in agroforestry systems were strongly correlated with each other (Figure 6), particularly with chemical properties, showing significant spatial correlation, which is consistent with the study by Da Silva et al (2018).…”

Section: Discussionsupporting

confidence: 90%

Agroforestry system construction in eastern coastal China: Insights from soil–plant interactions

Feng,

Liu,

et al. 2024

Land Degrad Dev

View full text Add to dashboard Cite

Agroforestry, as a phytoremediation measure, shows great potential for mitigating land degradation by constructing multidimensional and efficient agroforestry composite systems through regulating the microenvironment of agroforestry sites and improving soil properties. However, the effects of different agroforestry composite management modes on saline soils and the interactions between soil–plant systems under salt stress conditions in coastal areas remain largely unexplored. In this study, two salt‐tolerant tree species (Sapium sebiferum (Linn.) Roxb and Zelkova serrata (Thunb.) Makino) and four crop species (Medicago sativa, Sesbania cannabina, Sorghum bicolour, and Avena sativa) were selected for intercropping in eight composite patterns via field experiments, with dynamics of soil physicochemical properties and crop photosynthesis observed. The results showed that treatments intercropped with M. sativa had the highest soil bulk density range (1.41–1.48 g cm−3). The dynamics of topsoil (0–10 cm) chemical properties showed similar change patterns among treatments, whereas those of the 10–40 cm soil chemical properties (especially soil pH, soil organic matter [SOM], and total nitrogen [TN]) showed heterogeneity. Moreover, planting S. sebiferum (L.) Roxb under the same crop conditions increased tree height growth rate and survival rate by 75%–114% and 14%–33%, respectively, relative to planting Z. serrata (T.) Makino. Furthermore, a significant negative correlation was observed between soil moisture with crop intercellular CO2 concentration (λ = −0.77), while significant positive correlations were found between crop net photosynthetic rate (Pn) with soil TN (λ = 0.71), as well as SOM with atmospheric CO2 content (λ = 0.72). Structural equation modeling showed significant direct effects between tree height growth rate with soil TN and SOM. Soil moisture (λ = 0.47) and tree height growth rate (λ = 0.53) were dominant drivers of crop Pn. Our findings provide useful information for the prevention of coastal saline soil degradation and sustainable development of agroforestry.

show abstract

Section: Discussionsupporting

confidence: 90%

Agroforestry system construction in eastern coastal China: Insights from soil–plant interactions

Feng,

Liu,

et al. 2024

Land Degrad Dev

View full text Add to dashboard Cite

show abstract

“…The geostatistics plays an important role as an efficient technique for soil fertility assessment, since the soil management and conservation in agroforestry systems and other kinds of soil coverages depends on the efficiency in the soil evaluation (Moshia et al 2014). However, only a few studies have been developed with focus to spatial variability of soil atributes under agroforestry system aiming to auxiliate the management of soil protection and fertilization (Silva et al 2016;Silva et al 2018;Panday et al 2019). Therefore, the present study assessed the spatial variability of soil chemical attributes in an area of agroforestry system (AFS) compared to an adjacent forest (FOR), as a reference area, in the Municipality of Tomé-açu, Eastern Amazon, Brazil.…”

Section: Introductionmentioning

confidence: 99%

Spatial variability of soil fertility under agroforestry system and native forest in eastern Amazonia, Brazil

et al. 2023

View full text Add to dashboard Cite

The usage of spatial tools might be helpful in the optimization of decision-making regarding soil management, with technologies that assist in the interpretation of information related to soil fertility. Therefore, the present study evaluated the spatial variability of chemical attributes of the soil under an agroforestry system compared to a native forest in the municipality of Tomé-açu, Eastern Amazon, Brazil. Soil samples were performed at 36 points arranged in a 55 x 55 m grid. The soils were prepared and submitted to analysis in order to determine pH in H2O, exchangeable calcium, magnesium, potassium and aluminium, available phosphorus, potential acidity, organic matter, bases saturation and aluminium saturation. For each soil attribute, the spherical, gaussian and exponential models were adjusted. After the semivariograms fitting, data interpolation for assessment of spatial variability of the variables was performed through ordinary kriging. The spherical and gaussian models were the most efficient models in estimation of soil attributes spatial variability, in most cases. Most of variables presented a regular spatial variability in their respective kriging maps, with some exceptions. In general, the kriging maps can be used, and we can take them as logistical maps for management and intervention practices in order to improve the soil fertility in the study areas. The results principal components indicate the need for integrated management of soil chemical attributes, with localized application of acidity correctors, fertilizers and other types of incomes, using the spatial variability of these fertility variables.

show abstract

“…First, to analyze the structure of spatial dependence, the semivariogram was obtained for each variable. Based on the models presented by Silva et al (2018), three theoretical models were fitted and tested: spherical, exponential, and Gaussian. After confirming the structure of spatial dependence and fitting the model for each variable, ordinary kriging was used to estimate the variables in non-sampled sites, enabling the construction of the maps (Vieira, 2000;Silva et al, 2020).…”

Section: Statistical and Geostatistical Analysismentioning

confidence: 99%

Soil classes and properties explain the occurrence and fruit production of Brazil nut

Silva¹,

Silva²,

Wadt³

et al. 2021

Revista Brasileira De Ciência Do Solo

Self Cite

View full text Add to dashboard Cite

Soil properties and classes can influence the occurrence of plants and the production of Brazil nut fruits and may have a different distribution between sites. This study aimed to evaluate the relationship of plants' occurrence, production of Brazil nut fruits, and spatial variability of the properties in different soil classes in two Brazil nut stand in the state of Acre, Brazil. The study was conducted in two plots in two native Brazil nut stand, Cachoeira (CP01 and CP02 -plots 1 and 2) and Filipinas (FP01 and FP02 -plots 1 and 2). The soil profiles were described morphologically. Sixty soil samples were collected in each plot. The chemical properties, granulometry, soil density, particle density, and estimated total porosity were determined. The average fruit production was calculated by counting the fruits in a sample of Brazil nut trees. Subsequently, the trees were divided into three classes of production: low (≤1.5 can; the can unit has 18-L, which is able to hold 59 and 77 fruits, respectively, for Cachoeira and Filipinas), medium (1.6 to 3.9 cans), and high (≥4.0 cans). The can unit is the traditional measure of volume in the region and varies according to the locality. Cluster analysis was performed to determine whether there was a difference between Brazil nut stands and soil profiles, and geostatistics was used to evaluate the spatial dependence of soil properties. The highest occurrence of Brazil nut trees with high fruit production (≥4.0 cans) was found in the Latossolo Vermelho Distrófico argissólico (Oxisol) and Argissolo Vermelho-Amarelo Distrófico típico (Ultisol). However, the Argisol also hosted the plants with the lowest productions (≤1.5 can). The pH, total organic carbon, sum of bases, P, N, granulometry, and porosity showed a greater spatial variability, and FP02 showed a greater number of properties with high spatial variability compared to the other areas. Although the occurrence of plants and the production of Brazil nut fruits (Bertholletia excelsa) were associated with the classes and the physical and chemical properties of the soil, pyxidium production differed between areas. In general, soil physical properties were limiting factors for Brazil nut production and/or higher tree occurrence. Filipinas environment showed a low fruit production and a greater spatial variability of soil properties compared to Cachoeira.

show abstract

Spatial dependency and correlation of properties of soil cultivated with oil palm, Elaeis guineensis, in agroforestry systems in the eastern Brazilian Amazon

Cited by 8 publications

References 17 publications

Agroforestry system construction in eastern coastal China: Insights from soil–plant interactions

Agroforestry system construction in eastern coastal China: Insights from soil–plant interactions

Spatial variability of soil fertility under agroforestry system and native forest in eastern Amazonia, Brazil

Soil classes and properties explain the occurrence and fruit production of Brazil nut

Contact Info

Product

Resources

About